Multiple routing domains are unexceptionally included in the IP network, the ATM (Asynchronous Transmission Mode) network or the emerging ASON
(Automatic Switched Optical Network).
For the sake of scalability and security, internal topology information of each routing domain can be advertised to other routing domains in the network only after being aggregated by means of some topology aggregation method. Thus, each routing domain only maintains its own detailed topology information as well as aggregated topology information of other routing domains, thereby reducing the amount of information needing to be advertised and stored in the network.
Generally, a topology aggregation process includes firstly constructing a full-mesh topology composed of border nodes based on a real topology, and further compressing, which is optional, the full-mesh topology into a sparser topology, such as a star topology, a tree topology and the like.
FIG. 1 shows an example of a topology aggregation process. As shown in FIG. 1, topology 100 is a real topology comprising eight nodes 1-8, ten links, and two working wavelengths λ1 and λ2. In FIG. 1, the Nodes 1-4 are border nodes connected to external peer domains, the Nodes 5-8 are internal nodes, the solid line/the dashed line between nodes indicates the wavelength λ1/λ2 path of the link is free and a new connection can be established.
During the topology aggregation, internal nodes of topology 100 are concealed, and only border nodes 1-4 and resource availability therebetween are reserved. The connectivity relation among these four border nodes can be represented by a connectivity matrix as shown in formula (1).
                                          Matrix            ⁡                          (                              λ                1                            )                                =                      [                                                            -                                                  0                                                  1                                                  1                                                                              0                                                  -                                                  0                                                  0                                                                              1                                                  0                                                  -                                                  1                                                                              1                                                  0                                                  1                                                  -                                                      ]                          ,                                  ⁢                              Matrix            ⁡                          (                              λ                2                            )                                =                      [                                                            -                                                  1                                                  1                                                  0                                                                              1                                                  -                                                  1                                                  0                                                                              1                                                  1                                                  -                                                  0                                                                              0                                                  0                                                  0                                                  -                                                      ]                                              formula        ⁢                                  ⁢                  (          1          )                    
Topology 101 shown in FIG. 1 has 4 border nodes 1-4, and thus the connectivity among border nodes can be represented by a 4×4 matrix for each wavelength λ1 and λ2. If there is a logical link enabling two border nodes to be connected (for example, node 1 and node 4 can be connected with each other through wavelength λ1 path 1-5-6-3-4), the corresponding element of the matrix is set to 1, and 0 otherwise.
Topology 101, which includes only border nodes 1-4, is a full-mesh topology constructed in accordance with the connectivity matrix. It can be seen that the number of links is reduced to 5 after the full-mesh topology construction (in the worst case, the number of links is 6, i.e., all nodes are connected).
Topology 102 is the resultant topology after further compressing the topology 101. The redundant logical links in the former topology 101 are deleted, for example, the logical link of wavelength λ1 between node 3 and node 4 is replaced with the path 3-1-4, and the logical link of wavelength λ2 between node 2 and node 3 is replaced with the path 2-1-3. After compressing, the total number of links is further reduced to 3.
The existing topology aggregation technology is designed for the ATM network. There are three familiar methods, including the symmetric-node approach, the full-mesh approach and the star approach. The main idea of the symmetric-node approach is that all border nodes of the real topology are merged into a single virtual node and the connection property between border nodes is represented by a certain common value. The advantage of this approach is that only a very little amount of information needs to be exchanged. However, the disadvantage is that the provided information is too rough and inaccurate excessively, which will cause that the intra-domain resources can't be utilized appropriately. The full-mesh approach aims at the accuracy of the aggregation information. It assumes that all border nodes of the real topology are full connected by logical links, each of which is configured with one or more QoS parameters, such as delay or bandwidth. This approach reserves the connectivity property between border nodes of the original real topology accurately. However, because it must maintain the information of N(N-1)/2(N is the number of border nodes) logical links, when the network size is relatively large, the scalability is poor. The star approach assumes that there is a virtual node in the center, and all the border nodes in real topology are connected to it by logical links. Furthermore, each logical link may have different property. Thus, the star approach can represent more detailed link information, and may be much more accurate than the symmetric-node approach. At the same time, the star approach only needs to maintain the information of N logical links, and thus has better scalability than the full-mesh approach and is suitable for a relatively larger network.
However, when the above-mentioned topology aggregation methods designed for the ATM network are applied to the optical network, these methods will be too rough and inaccurate to reach a good performance as a condition of wavelength continuity constraint needs to be met. Therefore, a more suitable solution for topology aggregation is required for the optical network such as ASON.